Thermal super-pixels for bimodal stress recognition

Ramin Irani, Kamal Nasrollahi, Abhinav Dhall, Thomas B. Moeslund, Tom Gedeon

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

10 Citations (Scopus)


Stress is a response to time pressure or negative environmental conditions. If its stimulus iterates or stays for a long time, it affects health conditions. Thus, stress recognition is an important issue. Traditional systems for this purpose are mostly contact-based, i.e., they require a sensor to be in touch with the body which is not always practical. Contact-free monitoring of the stress by a camera [1], [2] can be an alternative. These systems usually utilize only an RGB or a thermal camera to recognize stress. To the best of our knowledge, the only work on fusion of these two modalities for stress recognition is [3] which uses a feature level fusion of the two modalities. The features in [3] are extracted directly from pixel values. In this paper we show that extracting the features from super-pixels, followed by decision level fusion results in a system outperforming [3]. The experimental results on ANUstressDB database show that our system achieves 89% classification accuracy.

Original languageEnglish
Title of host publication2016 Sixth International Conference on Image Processing Theory, Tools and Applications
Subtitle of host publicationIPTA 2016, Oulu, Findland, December 2016
EditorsMiguel Bordallo Lopez, Abdenour Hadid, Matti Pietikainen
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781467389105
ISBN (Print)9781467389112
Publication statusPublished - 2017
Externally publishedYes
EventInternational Conference on Image Processing Theory, Tools and Applications (IPTA) 2016 - Oulu, Finland
Duration: 12 Dec 201615 Dec 2016
Conference number: 6th


ConferenceInternational Conference on Image Processing Theory, Tools and Applications (IPTA) 2016
Abbreviated titleIPTA 2016
Internet address


  • Facial Expression
  • RGB Images
  • Stress Recognition
  • Super-pixels
  • Thermal Images

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